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Horizon-AGN virtual observatory - 2: Template-free estimates of galaxy properties from colours

Davidzon, I. and Laigle, C. and Capak, P. L. and Ilbert, O. and Masters, D. C. and Hemmati, S. and Apostolakos, N. and Coupon, J. and de la Torre, S. and Devriendt, J. and Dubois, Y. and Kashino, D. and Paltani, S. and Pichon, C. (2019) Horizon-AGN virtual observatory - 2: Template-free estimates of galaxy properties from colours. . (Unpublished)

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Using the Horizon-AGN hydrodynamical simulation and self-organising maps (SOMs), we show how to compress the complex data structure of a cosmological simulation into a 2-d grid which is much easier to analyse. We first verify the tight correlation between the observed 0.3−5μm broad-band colours of Horizon-AGN galaxies and their high-resolution spectra. The correlation is found to extend to physical properties such as redshift, stellar mass, and star formation rate (SFR). This direct mapping from colour to physical parameter space is shown to work also after including photometric uncertainties that mimic the COSMOS survey. We then label the SOM grid with a simulated calibration sample and estimate redshift and SFR for COSMOS-like galaxies up to z∼3. In comparison to state-of-the-art techniques based on synthetic templates, our method is comparable in performance but less biased at estimating redshifts, and significantly better at predicting SFRs. In particular our "data-driven" approach, in contrast to model libraries, intrinsically allows for the complexity of galaxy formation and can handle sample biases. We advocate that obtaining the calibration for this method should be one of the goals of next-generation galaxy surveys.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper
Davidzon, I.0000-0002-2951-7519
Capak, P. L.0000-0003-3578-6843
Ilbert, O.0000-0002-7303-4397
Masters, D. C.0000-0001-5382-6138
Hemmati, S.0000-0003-2226-5395
Kashino, D.0000-0001-9044-1747
Additional Information:ID thanks Stefano Andreon, Sirio Belli, Micol Bolzonella, Keerthana Jegatheesan, Chris Hayward, and Lucia Pozzetti for useful discussions. CL is supported by a Beecroft Fellowship. OI acknowledges the funding of the French Agence Nationale de la Recherche for the project "SAGACE". This research was supported in part by the National Science Foundation under Grant No. NSF PHY-1748958 and by the NASA ROSES grant 12-EUCLID12-0004. The analysis presented in this work relied on the HPC resources of CINES (Jade) under the allocation 2013047012 and c2014047012 made by GENCI and on the Horizon and CANDIDE clusters hosted by Institut d'Astrophysique de Paris. We warmly thank S. Rouberol for maintaining these clusters on which the simulation was post-processed. This research is part of ERC grant 670193 and horizon-UK and is also partly supported by the Centre National d'Etudes Spatiales (CNES). Several python packages were used, including ASTROPY (Astropy Collaboration et al. 2013; Price-Whelan et al. 2018) and SOMPY (main contributors: Vahid Moosavi, Sebastian Packmann, Iván Vállas).
Group:Infrared Processing and Analysis Center (IPAC)
Funding AgencyGrant Number
Beecroft FellowshipUNSPECIFIED
Agence Nationale de la Recherche (ANR)SAGACE
European Research Council (ERC)670193
Centre National d'Études Spatiales (CNES)UNSPECIFIED
Subject Keywords:galaxies: formation,evolution - methods: statistical, data analysis
Record Number:CaltechAUTHORS:20190813-094655165
Persistent URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:97859
Deposited By: Tony Diaz
Deposited On:13 Aug 2019 18:35
Last Modified:03 Oct 2019 21:35

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